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Oncotarget ; 6(14): 12783-95, 2015 May 20.
Article in English | MEDLINE | ID: mdl-25904052

ABSTRACT

Cancer molecular heterogeneity might explain the variable response of EGFR mutant lung adenocarcinomas to tyrosine kinase inhibitors (TKIs). We assessed the mutational status of 22 cancer genes by next-generation sequencing (NGS) in poor, intermediate or good responders to first-line gefitinib. Clinical outcome was correlated with Additional Coexisting Mutations (ACMs) and the EGFR Proportion of Mutated Alleles (PMA). Thirteen ACMs were found in 10/17 patients: TP53 (n=6), KRAS (n=2), CTNNB1 (n=2), PIK3CA, SMAD4 and MET (n=1 each). TP53 mutations were exclusive of poor/intermediate responders (66.7% versus 0, p=0.009). Presence of ACMs significantly affected both PFS (median 3.0 versus 12.3 months, p=0.03) and survival (3.6 months versus not reached, p=0.03). TP53 mutation was the strongest negative modifier (median PFS 4.0 versus 14.0 months). Higher EGFR PMA was present in good versus poor/intermediate responders. Median PFS and survival were longer in patients with EGFR PMA ≥0.36 (12.0 versus 4.0 months, p=0.31; not reached versus 18.0 months, p=0.59). Patients with an EGFR PMA ≥0.36 and no ACMs fared significantly better (p=0.03), with a trend towards increased survival (p=0.06). Our exploratory data suggest that a quantitative (PMA) and qualitative (ACMs) molecular heterogeneity assessment using NGS might be useful for a better selection of patients.


Subject(s)
Adenocarcinoma/genetics , Antineoplastic Agents/therapeutic use , Drug Resistance, Neoplasm/genetics , Genes, erbB-1/genetics , Lung Neoplasms/genetics , Quinazolines/therapeutic use , Adenocarcinoma/drug therapy , Adenocarcinoma/mortality , Adenocarcinoma of Lung , Adult , Aged , Aged, 80 and over , DNA Mutational Analysis , Disease-Free Survival , Female , Gefitinib , High-Throughput Nucleotide Sequencing , Humans , Kaplan-Meier Estimate , Lung Neoplasms/drug therapy , Lung Neoplasms/mortality , Male , Middle Aged , Multiplex Polymerase Chain Reaction , Mutation , Proportional Hazards Models , Sequence Analysis, DNA
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